Understanding spatial accessibility and facility crowdedness is central to public service planning, yet existing methods often treat these two metrics separately. The Two-Step Floating Catchment Area (2SFCA) method measures accessibility from the demand side, while the inverted 2SFCA (i2SFCA) assesses crowdedness from the supply side. Without proper integration, these two measures may diverge, raising concerns of their validity. This study introduces a distance decay parameterization framework to reconcile 2SFCA and i2SFCA by optimizing a unified distance decay function through cross-entropy minimization. It demonstrates that aligning demand-side and supply-side flows effectively enforces a behavioral equilibrium between accessibility and crowdedness. A case study using inpatient hospital flow data in Florida shows that the ‘reconciled 2SFCA (r2SFCA) model’ achieves strong alignment between estimated and observed service flows while maintaining simplicity in its formulation. These findings validate the self-organizing nature of human service-seeking behaviors and support a unified, entropy-based calibration strategy for accessibility modeling.

Persistent disparities in access to maternal healthcare across the United States, particularly in rural and underserved communities, have resulted in poor maternal outcomes. Traditional statistical methods, such as Quadratic Programming (QP), have been utilized for healthcare resource reallocation, but they struggle with dynamic, multi-objective geographic optimization problems. This study presents a Reinforcement Learning (RL)-based framework to optimize maternity care resource distribution. We follow the Maximal Accessible Equality Problem (MAEP), aiming to enhance spatial equality by reducing the weighted accessibility variance. We integrate the Two-Step Floating Catchment Area (2SFCA) method for measuring maternity care accessibility and leverage Proximal Policy Optimization (PPO) to dynamically reallocate obstetric facilities across counties in Florida. To account for real-world complexities, we tested our RL framework under three scenario objectives: minimizing distance, obstetric bed supply preservation, and prioritizing underserved counties. Results show the proposed framework effectively reduces accessibility variance by 31.7–49.3%. These findings highlight the potential of RL in offering scalable, data-driven solutions to support equitable maternity health care, benefiting practical applications for implementing actionable health policy decision making.

Uneven distributions of population and service providers lead to geographic disparity in access for residents and varying workload for staff in facilities. The former can be captured by spatial accessibility in the traditional two-step floating catchment area (2SFCA) method; and the latter can be measured by potential crowdedness in the newly developed inverted 2SFCA (or i2SFCA) method. Residents-based accessibility and facility crowdedness are two sides of the same coin in examining the geographic variability of resource allocation. This short research note derives the formulations of both methods to solidify their theoretical foundation, and uses a case study to validate both. By doing so, the 2SFCA and i2SFCA are fully integrated into one conceptual framework, derived with extensions to the Huff model, and validated by empirical data.

The COVID-19 (coronavirus disease 2019) pandemic has expanded telehealth utilization in unprecedented ways and has important implications for measuring geographic access to healthcare services. Established measures of geographic access to care have focused on the spatial impedance of patients in seeking health care that pertains to specific transportation modes and do not account for the underlying broadband network that supports telemedicine and e-health. To be able to measure the impact of telehealth on healthcare access, we created a pilot augmentation of existing methods to incorporate measures of broadband accessibility to measure geographic access to telehealth. A reliable measure of telehealth accessibility is important to enable policy analysts to assess whether the increasing prevalence of telehealth may help alleviate the disparities in healthcare access in rural areas and for disadvantaged populations, or exacerbate the existing gaps as they experience "double burdens."